The Face API available from Microsoft's Azure suite of services is an AI service that analyzes faces in images. It is used to embed facial recognition into apps for a secured user experience. No machine-learning expertise is required. Features include face detection that perceives facial features and attributes—such as a face mask, glasses, or face location—in an image, and identification of a person by a match to a private repository or via photo ID.
$0.40
per 1,000 transactions (100M+ transactions)
National Instruments Vision Builder AI
Score 10.0 out of 10
N/A
National Instruments offers Visual Builder for Automated Instruction (AI) for creating machine vision applications.
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Pricing
Azure Face API
National Instruments Vision Builder AI
Editions & Modules
Standard
$0.40
per 1,000 transactions (100M+ transactions)
Standard
$0.60
per 1,000 transactions (5-100M transactions)
Standard
$0.80
per 1,000 transactions (1-5M transactions)
Standard
$1
per 1,000 transactions (0-1M transactions)
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Azure Face API
National Instruments Vision Builder AI
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
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Azure Face API
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Azure Face API
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National Instruments Vision Builder AI
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It all comes down to tradeoffs. Do you want something that is extremely flexible and full-featured or do you want something that is easy and fast to use? Sure there are things that you can't do in Vision Builder AI that you can implement in LabVIEW, however, the vast majority …
The perfect scenario is a production environment where items are passing in front of a camera on some type of conveyor system. Vision Builder AI can be set up to inspect those items and make decisions that can be handled down the line (rejection, sorting, etc.). It's great if you have an isolated vision system as part of a larger system that needs to just pass on results. It's not as well suited if you need that code tightly coupled with other code, such as vision-guided robotics.
It all comes down to tradeoffs. Do you want something that is extremely flexible and full-featured or do you want something that is easy and fast to use? Sure there are things that you can't do in Vision Builder AI that you can implement in LabVIEW, however, the vast majority of the applications that we work on do not need that extra functionality so Vision Builder AI is the best choice for us. If we find out along the way that Vision Builder AI is not going to work for us at least we have all of the steps and parameters figured out that we can use when moving to LabVIEW.